Validation of ash cloud modelling with satellite retrievals: a case study of the 16–17 June 1996 Mount Ruapehu eruption

Liu, J.; Salmond, Jennifer; Dirks, Kim N.; Lindsay, Jan M.

doi:10.1007/s11069-015-1753-3

Cited by 3 publications

(3 citation statements)

References 39 publications

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“…Isopachs and isopleths from deposits produced by a range of magmatic eruption styles at Tongariro and Ruapehu provide an approximate guide to potential tephra hazard scenarios (Topping 1973;Donoghue et al 1995a;Donoghue and Neall 1996;Bonadonna et al 2005;Pardo et al 2012aPardo et al , 2012bPardo et al , 2014Heinrich et al 2020a). At Ruapehu, hazard modelling has improved scenario development for larger eruptions, with a focus on ash fall and lahars (Cronin et al 1998;Hurst and Turner 1999;Turner and Hurst 2001;Lecointre et al 2004;Manville and Cronin 2007;Carrivick et al 2009;Graettinger et al 2010;Procter et al 2010Procter et al , 2012Liu et al 2015).…”

Section: Larger Magmatic Eruptionsmentioning

confidence: 99%

Ruapehu and Tongariro stratovolcanoes: a review of current understanding

Leonard

Christenson

et al. 2021

New Zealand Journal of Geology and Geophysics

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Ruapehu (150 km 3 cone, 150 km 3 ring-plain) and Tongariro (90 km 3 cone, 60 km 3 ring-plain) are iconic stratovolcanoes, formed since ∼230 and ∼350 ka, respectively, in the southern Taupo Volcanic Zone and Taupo Rift. These volcanoes rest on Mesozoic metasedimentary basement with local intervening Miocene sediments. Both volcanoes have complex growth histories, closely linked to the presence or absence of glacial ice that controlled the distribution and preservation of lavas. Ruapehu cone-building vents are focused into a short NNE-separated pair, whereas Tongariro vents are more widely distributed along that trend, the differences reflecting local rifting rates and faulting intensities. Both volcanoes have erupted basaltic andesite to dacite (53-66 wt.% silica), but mostly plagioclase-two pyroxene andesites from storage zones at 5-10 km depth. Erupted compositions contain evidence for magma mixing and interaction with basement rocks. Each volcano has an independent magmatic system and a growth history related to long-term (>10 4 years) cycles of mantlederived magma supply, unrelated to glacial/interglacial cycles. Historic eruptions at both volcanoes are compositionally diverse, reflecting small, dispersed magma sources. Both volcanoes often show signs of volcanic unrest and have erupted with a wide range of styles and associated hazards, most recently in 2007 (Ruapehu) and 2012 (Tongariro).

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Section: Larger Magmatic Eruptionsmentioning

confidence: 99%

Ruapehu and Tongariro stratovolcanoes: a review of current understanding

Leonard

Christenson

et al. 2021

New Zealand Journal of Geology and Geophysics

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“…3. The 17 June 1996 eruption of Ruapehu produced a classic weak plume that was modeled by , Hurst and Turner (1999), Scollo et al (2008), Liu et al (2015), and Klawonn et al (2014), among oth-ers. The main phase involved two pulses, one beginning 16 June at 19:10 UTC and lasting 2.5 h and the second at 23:00 UTC and lasting approximately 1.5 to 2 h. Ash-laden plumes reached to about 8.5 km a.m.s.l.…”

Section: Background On the Depositsmentioning

confidence: 99%

“…Although one VATD model, Fall3d, calculates aggregation during transport for research studies Costa et al, 2010), no operational models consider it. Instead, aggregation is accounted for by either setting a minimum settling velocity in the code (Carey and Sigurdsson, 1982;Hurst and Turner, 1999;Armienti et al, 1988;Macedonio et al, 1988), or, in the model input, adjusting particle-size distribution by replacing some of the fine ash with aggregates of a specified density, shape, and size range (Bonadonna et al, 2002;Cornell et al, 1983;Mastin et al, 2013b). These strategies will probably prevail for at least the next few years, until microphysical algorithms replace them.…”

Section: Introductionmentioning

confidence: 99%

Adjusting particle-size distributions to account for aggregation in tephra-deposit model forecasts

Mastin¹,

Eaton²,

Durant³

2016

Atmos. Chem. Phys.

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Abstract. Volcanic ash transport and dispersion (VATD) models are used to forecast tephra deposition during volcanic eruptions. Model accuracy is limited by the fact that fine-ash aggregates (clumps into clusters), thus altering patterns of deposition. In most models this is accounted for by ad hoc changes to model input, representing fine ash as aggregates with density ρagg, and a log-normal size distribution with median μagg and standard deviation σagg. Optimal values may vary between eruptions. To test the variance, we used the Ash3d tephra model to simulate four deposits: 18 May 1980 Mount St. Helens; 16–17 September 1992 Crater Peak (Mount Spurr); 17 June 1996 Ruapehu; and 23 March 2009 Mount Redoubt. In 192 simulations, we systematically varied μagg and σagg, holding ρagg constant at 600 kg m−3. We evaluated the fit using three indices that compare modeled versus measured (1) mass load at sample locations; (2) mass load versus distance along the dispersal axis; and (3) isomass area. For all deposits, under these inputs, the best-fit value of μagg ranged narrowly between ∼  2.3 and 2.7φ (0.20–0.15 mm), despite large variations in erupted mass (0.25–50 Tg), plume height (8.5–25 km), mass fraction of fine ( <  0.063 mm) ash (3–59 %), atmospheric temperature, and water content between these eruptions. This close agreement suggests that aggregation may be treated as a discrete process that is insensitive to eruptive style or magnitude. This result offers the potential for a simple, computationally efficient parameterization scheme for use in operational model forecasts. Further research may indicate whether this narrow range also reflects physical constraints on processes in the evolving cloud.

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Monitoring Volcanic Plumes and Clouds Using Remote Sensing: A Systematic Review

Mota,

Pacheco,

Pimentel

et al. 2024

Remote Sensing

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Volcanic clouds pose significant threats to air traffic, human health, and economic activity, making early detection and monitoring crucial. Accurate determination of eruptive source parameters is crucial for forecasting and implementing preventive measures. This review article aims to identify the most common remote sensing methods for monitoring volcanic clouds. To achieve this, we conducted a systematic literature review of scientific articles indexed in the Web of Science database published between 2010 and 2022, using multiple query strings across all fields. The articles were reviewed based on research topics, remote sensing methods, practical applications, case studies, and outcomes using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Our study found that satellite-based remote sensing approaches are the most cost-efficient and accessible, allowing for the monitoring of volcanic clouds at various spatial scales. Brightness temperature difference is the most commonly used method for detecting volcanic clouds at a specified temperature threshold. Approaches that apply machine learning techniques help overcome the limitations of traditional methods. Despite the constraints imposed by spatial and temporal resolution and optical limitations of sensors, multiplatform approaches can overcome these limitations and improve accuracy. This study explores various techniques for monitoring volcanic clouds, identifies research gaps, and lays the foundation for future research.

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Validation of ash cloud modelling with satellite retrievals: a case study of the 16–17 June 1996 Mount Ruapehu eruption

Cited by 3 publications

References 39 publications

Ruapehu and Tongariro stratovolcanoes: a review of current understanding

Ruapehu and Tongariro stratovolcanoes: a review of current understanding

Adjusting particle-size distributions to account for aggregation in tephra-deposit model forecasts

Monitoring Volcanic Plumes and Clouds Using Remote Sensing: A Systematic Review

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